The cloud, agriculture, and the rest of us: some valuable lessons

December 16, 2014 by Olivier Blanchard - No Comments

Today, I though I would show you something cool again, and pretty different from the sort of stuff that you usually hear about when people like me talk about new tech or clever business practices. You have probably noticed that I spend a good deal of time thinking and talking about cloud computing, systems of systems, and the unfortunately named “internet of things.” (Great concept, absolutely real, super important… but that term… ugh… it was a cringe-worthy buzzword long before mainstream journalists started using it.) Anyway, I don’t want to bore you with stuff that you already know and stuff that you’ve already read. You don’t need me to tell you that the cloud frees small and mid-sized companies from massive (and cost-prohibitive) investments in IT infrastructure. You probably already know about hybridized IT (adding cloud capacity to legacy IT infrastructure so you don’t have to start over). My CMO and the Cloud series already focuses on business applications and how cloud is changing marketing anyway. Keep reading it and you will have all the insights you need to have productive meetings with your IT pros. Today, I want to take you out of the office completely. I want you to put on some rugged boots, lose the ID keycard, grab some sunglasses, and go on a little road trip with me, because I have something cool to show you.

Farms are businesses too. Here is how farmers are using the cloud:

I know you aren’t going to leave your office job to become a farmer. I mean… if you want to, cool. We can always use more farmers (and ranchers). But… this isn’t about that. This is about stepping outside your sandbox for a few minutes and seeing how other people, completely outside of your normal circles, are leveraging cloud tech (in conjunction with other tech) to solve real world problems. It’s a good exercise. Most of the instances in which I helped a company or a project team find a creative solution to a problem that had stumped them for far too long started with a road trip (real or virtual). Looking into how other people in other industries solve problems usually gives you insights into how to solve yours.

So anyway… farming. Pretty important stuff, because, you know… food. And roughly 40% of the world’s workforce works in agriculture. When you’re a farmer, tons of variables can affect your business, and notably weather, which can be pretty hard to predict, as you well know. The old school model was to plant and pray (and if prayer wasn’t your thing, hope for the best). Good farmers knew how to use almanacs and read the land and relied on a pretty good gut feeling about what kind of seasons were ahead, but even the most accomplished weather whisperer was just kind of making an educated guess, using data that was… well… pretty thin. And you know, there’s something to be said for the old ways. I have a lot of respect for farmers who managed to make it work on nothing but hard work, experience and instinct. But, as you well know, farming wasn’t as competitive back in the day, and the climate tended to be a little more predictable, so… new challenges called for new solutions, and some enterprising folks came up with just the thing. Here are a few examples of what I am talking about (and no, this is most definitely not a product review):

Field Mapping:

Okay, you could just pace your fields. And if the zombie apocalypse actually happens at some point, you might have to go back to that. But until then, you can use GPS-assisted field mapping software that requires very little gear (all super portable) and feeds into a smartphone app. From there, the data gets processed in the cloud, and the phone app helps the farmer with all sorts of useful things like field management, crop rotation history, compare the original plan with actual results, and so on.

Tracking rainfall:

Field mapping and managing crop history are pretty handy, but tracking rainfall is also pretty key. Remember that the more data you have, the more data you (or an analytics product) can crunch for you. Instead of writing it down in a physical diary or entering the data into an Excel sheet, you can use your smart phone to do it, and the cloud-based app will allow you to track rainfall trends in real time.

Operations management:

In addition to field mapping and rainfall tracking, farmers can now also keep track of material costs for each operation, analyze changes in soil composition, manage seed and materials storage data, manage planning, and so on. If your farm is large enough, you can also manage your fleet (you know… tractors and such) from your smart phone. Irrigation? Same thing.

Again, all of that data is stored and crunched in the cloud, with a simple interface accessible on a smart phone or tablet. Not too shabby.

Okay, now what?

Pretty cool stuff, right? Chances are that if you work in an office and don’t hang out with farmers, you don’t really think about how mobile and the cloud fit into farming operations. And if you take a step back from the tractors and the silos and the work boots, you might notice that these tools essentially do the exact same thing that apps designed to help you manage logistics in a retail or manufacturing or project management environment do. Managing a farming operation isn’t all that different from managing a shipping warehouse. Measuring rainfall and yield can’t really be all that different from measuring web traffic and mobile sales. It’s all the same thing, just tweaked a little to apply to a very specific type of business. What strikes me about all of this though (and not just in farming), is that much of it is still based on a “what did we already do, and what are we doing next?” mode of thinking. In other words, the data’s scope along a timeline is limited to the past, the present, and some guestimated notion of how, based on that information, doing X will result in Y. As awesome as it all is, it’s still just management. The planning piece isn’t super evolved yet. What is missing is an advanced predictive analysis system that will give farmers a better glimpse into what they need to do to get the most out of their farm, based on what their objectives are.

Imagine taking all of the above data and letting IBM’s Watson have a go at it, for instance. (In case you missed it, anyone can use Watson Analytics now. Finally.) After all, if Watson can help accelerate innovation in tech, cure cancer, and solve traffic congestion problems in major cities, it can certainly handle the now what? missing piece of the puzzle for farmers looking for the next game-changing cloud-based app. Right? Right. (You can read more about that here.)

But what about solving world hunger?

That’s a bigger topic than we have time to get into today (from logistics and politics to capacity and economics, we could spend years digging into the complexity of our global food system), but we can talk about one aspect of this issue that’s pretty cool, and that I think has particular value in the context of our discussion, and it has to do with how cloud and mobile technologies can help very small farms in emerging economies around the world. Because honestly, I can’t think of better real-world underdog success stories than those of smallholder farmers working in harsh climates and with only the most rudimentary infrastructure at their disposal, using tech like this to improve their odds of not only survival but success.

The first example of how data and mobile connectivity started giving farmers in low tech areas an edge can be be found a little more than a decade ago. The objective then was simply to help farmers keep track of market pricing for crops and livestock, so they wouldn’t get fleeced by buyers with better information. Programs started sprouting up around the world: mKisan in India and SonokiSMS64 in Kenya are prime examples. But as data and cloud-based services started to evolve, pricing information services began to evolve to incorporate other types of information, like weather, pest  and disease advisories, even how-to videos to help teach farmers techniques they may not be 100% knowledgeable about. While farmers with access to smartphones increasingly rely on apps (like iCow, for instance), SMS is still, in many parts of the world, a vital tool for farmers for whom information technology has been an economic and operational godsend. (You can read more about it here.)

As networks around the world continue to improve and smartphone prices drop, SMS will eventually be replaced by apps even in the most remote parts of the world, and on the back end, cloud capabilities. And as farmers become more able to collect, manage, share and analyze data, the more control they will have over not just their farming operations but their ability to connect and form partnerships with other farmers, NGOs, and agribusiness.

Speaking of agribusiness, big data, the cloud and mobility haven’t sparked the interest of only farmers. Major players in that space have also invested in it too, and for good reason. One notable example is Monsanto. In spite of the perpetual cloud of bad press that follows the agribusiness giant these days, what it is doing with big data, cloud and mobile is really smart and helpful, and looks beyond the obvious farm-by-farm specific data to track broader climate-change data around the world. Why? Because its agriculture sandbox is global, not just local or regional. Climate change being a global phenomenon, it’s important to track weather and farming data on a global scale, and one way to do that is to collect data from farmers all around the globe, then use that data to help them adapt to new trends in climate, rainfall, soil erosion, and so on, and provide these farmers with reliable insights into how they should start preparing for the sorts of climate adaptation challenges they will have to face in the coming decades. This kind of symbiotic relationship where buyers, sellers and farmers can enjoy an open exchange of data and information is precisely the sort of system of systems that cloud technologies and evolved analytics make possible. In regards to solving major human problems like world hunger, access to that amount of data and a degree of cooperation this massive can’t hurt; but more to the point, it would all be impossible to achieve without access to cloud and mobile technologies.

Also, as an FYI, the timing couldn’t be better. Per Mother Jones’ Tim McDonnell:

Efforts to increase crop yields are especially important in the developing world. The global population is projected to swell to more than 9 billion people by 2050—with over half of that growth in Africa. The UN Food and Agriculture Organization estimates that as a result, food production will have to increase by 70 percent. But according to the UN’s latest climate change report, South Asia and sub-Saharan African—the two regions with the most food insecurity—are actually expected to see an 8 percent drop in crop yields by 2050, thanks to rising temperatures and increasingly sporadic rainfall.

You can read all about that program here (and you really should).

Problems and solutions: because we’re all really just working on solving a problem, and using the right tools matters.

So… will cloud computing save the world and solve our food production problems? That’s a question you might have to ask Watson. Here’s how I look at it: we have a much better shot at solving complex problems with better and smarter tech than without it.

Now let’s circle back to why you really came here: you and your company. You and the problem that you are trying to solve. At its core, your company is no different from a farm. Your industry, like farming, is dealing with small nagging changes and very big existential ones. Some farms will fail and some businesses will fail. If you believe in luck or fate, that’s fine. If, like me, you believe that you tend to make your own luck (at least most of the time), then you know that being smart about the decisions you make has more effect on the outcome than a roll of the dice. Like farms, businesses that learn to adapt to change the fastest have the best chance of not only surviving but thriving. Being able to predict the weather and changes in climate allows you to adapt to that change early enough to plan for it properly. The smaller and more nimble the company, the faster the adaptation. You don’t necessarily need a huge window into the future to change course or shift your focus from one type of investment to another. The bigger the company (or system), the less nimble it is, the slower the adaptation. Being able to see further into the future allows you to make the necessary changes in the time it takes to make them, given the organization’s size and complexity. It isn’t really rocket science: you build the adaptive models you need to survive or get an edge on the competition, based on your goals, challenges and capabilities. And when tools that allow you to do that better and faster than ever before, you use them or you lose your farm. It’s as simple as that.

World hunger, rising oceans, real estate slumps, media fragmentation, shrinking budgets, competing against price-smashing imports, fickle consumers… everyone is working on solving a problem. If tools exist that can help solve these problems better and faster, use them. Is there a learning curve involved? Always. So what? If you think learning how to use new tools is hard, wait until you get a taste of failure. And look, if a smallholder farmer without the benefit of a business degree can adopt new technologies to improve his or her business – without ever having laid eyes on a server or set foot in a corporate meeting room, without having ever attended an industry conference or been advised by well paid consultants – what’s your organization’s excuse for lagging behind?

Poker this vs. poker that.

I will leave you with one final thought today, in case the farming analogy hasn’t really pulled the right levers: Imagine yourself sitting at a poker table with only yourself and your gut to rely on. Consider your odds against the other players (who might be a lot better at the game than you are).

Now imagine sitting at that same poker table, but with access to card-tracking data; insights into the other player’s betting behaviors and history, real-time heart rate and stress levels; and self-updating odds reports.

Which do you think is more likely to produce better results for you? The first option (intuition-based decision-making), or the second (analytics-based decision-making)?

You shouldn’t have to think too long and hard about it. Your business is no different. How much guessing do you really want to keep doing?

I hope that today’s focus helped put things in a clearer light for you. And if you learned something new about farming and global food production, that’s even better.

Cheers,

Olivier

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This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

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